Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Mahima Pushkarna"'
Publikováno v:
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems.
Artificial intelligence (AI) presents new challenges for the user experience (UX) of products and services. Recently, practitioner-facing resources and design guidelines have become available to ease some of these challenges. However, little research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1fd22f59e34238a2d4ee4c05f4bc7ad
https://doi.org/10.1145/3544548.3580900
https://doi.org/10.1145/3544548.3580900
Autor:
Steven M. Goodman, Erin Buehler, Patrick Clary, Andy Coenen, Aaron Donsbach, Tiffanie N. Horne, Michal Lahav, Robert MacDonald, Rain Breaw Michaels, Ajit Narayanan, Mahima Pushkarna, Joel Riley, Alex Santana, Lei Shi, Rachel Sweeney, Phil Weaver, Ann Yuan, Meredith Ringel Morris
Prior work has explored the writing challenges experienced by people with dyslexia, and the potential for new spelling, grammar, and word retrieval technologies to address these challenges. However, the capabilities for natural language generation de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba6b3be5e483b914e2f6967cbf2b6e05
Autor:
Ann Yuan, Ellen Jiang, Ian Tenney, Sebastian Gehrmann, Andy Coenen, Carey Radebaugh, Mahima Pushkarna, Tolga Bolukbasi, Emily Reif, James Wexler, Jasmijn Bastings
Publikováno v:
EMNLP (Demos)
We present the Language Interpretability Tool (LIT), an open-source platform for visualization and understanding of NLP models. We focus on core questions about model behavior: Why did my model make this prediction? When does it perform poorly? What
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5faca0b1a31434dc1de6cad0462d94d
http://arxiv.org/abs/2008.05122
http://arxiv.org/abs/2008.05122
Publikováno v:
FAT*
As more and more industries use machine learning, it's important to understand how these models make predictions, and where bias can be introduced in the process. In this tutorial we'll walk through two open source frameworks for analyzing your model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::355acff64b1aae7c0de5ae2db40963bc
https://doi.org/10.1145/3351095.3375662
https://doi.org/10.1145/3351095.3375662
Autor:
Jimbo Wilson, Fernanda B. Viégas, James Wexler, Martin Wattenberg, Mahima Pushkarna, Tolga Bolukbasi
Publikováno v:
IEEE transactions on visualization and computer graphics. 26(1)
A key challenge in developing and deploying Machine Learning (ML) systems is understanding their performance across a wide range of inputs. To address this challenge, we created the What-If Tool, an open-source application that allows practitioners t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f5b9302104f9c46b7da3803fdce3640
https://pubmed.ncbi.nlm.nih.gov/31442996
https://pubmed.ncbi.nlm.nih.gov/31442996